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  # Password security classifier
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- This is a keras model that gives a binary response showing how secure is a password. The `start.py` file has a `clf` function that inputs a string of a password and responds with a 0-1 float value. 1 means secure and 0 insecure.
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  I used this password list as a dataset + random password generation using the `random` library (I know, it's not very secure but this is for a dataset).
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  ## Model & Training
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  The model was trained on 4,2MiB of .csv data for 2 epochs on Adam with learning rate 0.00001, batch size 4 and mse loss.
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  ## Evaluation
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  The evaluation of the model on a test dataset shows:
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  **loss** -
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- **accuracy** -
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Password security classifier
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+ This is a keras model that gives a binary response showing how secure is a password.
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  I used this password list as a dataset + random password generation using the `random` library (I know, it's not very secure but this is for a dataset).
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  ## Model & Training
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  The model was trained on 4,2MiB of .csv data for 2 epochs on Adam with learning rate 0.00001, batch size 4 and mse loss.
 
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  ## Evaluation
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  The evaluation of the model on a test dataset shows:
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  **loss** -
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+ **accuracy** -
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+ ## Model usage
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+ The `start.py` file has a `clf` function that inputs a string of a password and responds with a 0-1 float value. 1 means secure and 0 insecure.
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+ To train the model, create a `dataset.csv` file. Here's an example:
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+ ```csv
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+ 0,qwerty
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+ 0,123456
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+ 1,ISOdvsjs8r8
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+ 1,F(SEsDLxc__
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+ ```
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+ After the `dataset.csv` file is created, now you can adjust the settings in the `net.py` file and run it.